Companies that own and operate computers for data processing encounter a need for capacity planning of computing resources, so that they can efficiently and accurately plan the purchasing of new computing resources. Computing resources include CPUs, memory, disk storage, tape storage, access devices, operating systems, file systems, and many others. Capacity planning relies on the accurate forecasting of resource utilization. Forecasting, in turn, requires analysis of current and historical system performance metrics data. These metrics include CPU utilization, disk storage utilization, memory utilization, memory allocation, file system access, and many others.
There are several issues of concern with regard to capacity planning. It is important for companies to be able to determine points at which new hardware will become necessary to meet system requirements. It is also important for companies to be able to project scenarios for potential configuration changes including both hardware and software. Another issue of concern is the monitoring and analysis of performance problems.
To address these and other needs, data analysis/reporting tools for analyzing, reporting, and graphing system performance data for the purposes of capacity forecasting and planning is currently commercially available. One such product that is widely used is SAS IT Service Vision software available from the SAS Institute, Inc. of Cary, N.C. However, performance data must be provided to SAS IT Service Vision in properly formatted SAS datasets. Likewise, specially formatted performance data is required by other commercially available data analysis software.
There are software products available, known as collection agents, that run on computers and collect raw performance data from computer resources. Examples of collection agents include Patrol available from BMC Corporation of Houston, Tex.; Unicenter TNG available from Computer Associates of Islandia, N.Y., BGS available from BMC Corporation, and Candle Availability Command Center from Candle Corporation. Most of the available collection agents may compile performance data into flat files known as Universal/Uniform Data Format (hereinafter UDF) files. A significant problem with available collection agents is the UDF files they produce are not properly formatted for use by data analysis/reporting tools such as SAS IT Service Vision. Furthermore, different types of collection agents may compile UDF files having different arrangements, using different variables and sequential ordering of variables. Data from the UDF files must be appropriately processed to produce properly formatted datasets that may be read and used by data analysis/reporting tools.
Heretofore, it has been necessary to process data from each type of collection agent in a unique way to produce properly formatted datasets. Often, a customized data processing program had to be written for each collection agent. Further complicating this task is the fact that a single UDF file contains data for many different types of performance metrics; these data must be sorted out into individual dataset tables for input to data analysis/reporting tools such as SAS IT Service Vision.
Accordingly, there is a need for single integrated product that can read performance data from many different types of collection agents and convert that performance data into properly formatted SAS datasets for use by data analysis/reporting tools irrespective of the type of collection agent that produced the performance data.